Performance of Null Handling in Array Databases

Array databases specialize in storage, management, and query processing on massive multidimensional array data such as satellite image time-series, weather forecast models, IoT sensor measurements, medical imaging data, etc. Some of the values in this data may be ”null” for a variety of reasons, such as unknown, known false, etc. The DBMS must handle null values correctly and efficiently. As of today, the effects of different data structures for representing null values on query processing in array databases have not been systematically studied. As a consequence, it is not clear what the optimal way for handling null values is. In this paper, we measure how four different methods for encoding null values perform across most common categories of array operations. The result is a comprehensive overview, publicly available in open source, providing relevant insights into the performance characteristics of these data structures allowing to discern which among them offers the most optimal approach for representing null values in an array processing context.